Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Liu, Longyao"'
Object detection is widely studied in computer vision filed. In recent years, certain representative deep learning based detection methods along with solid benchmarks are proposed, which boosts the development of related researchs. However, existing
Externí odkaz:
http://arxiv.org/abs/2104.13763
The one-shot Person Re-ID scenario faces two kinds of uncertainties when constructing the prediction model from $X$ to $Y$. The first is model uncertainty, which captures the noise of the parameters in DNNs due to a lack of training data. The second
Externí odkaz:
http://arxiv.org/abs/2104.09152
Caused by the difference of data distributions, intra-domain gap and inter-domain gap are widely present in image processing tasks. In the field of image dehazing, certain previous works have paid attention to the inter-domain gap between the synthet
Externí odkaz:
http://arxiv.org/abs/2102.03501
Few-shot object detection (FSOD) aims at learning a detector that can fast adapt to previously unseen objects with scarce annotated examples, which is challenging and demanding. Existing methods solve this problem by performing subtasks of classifica
Externí odkaz:
http://arxiv.org/abs/2011.14667
Publikováno v:
In Neurocomputing 7 May 2022 485:1-11
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Publikováno v:
Applied Intelligence; Jun2023, Vol. 53 Issue 12, p15080-15094, 15p